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      Recruiting migrant workers in Australia for Public Health surveys: how sampling strategy make a difference in estimates of workplace hazards

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      BMC Research Notes
      BioMed Central
      Migrant workers, Cross-sectional surveys, Sampling, Methods

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          Abstract

          Objectives

          One third of the Australian work force are immigrants. Relatively little is known about working conditions for specific migrant groups. The objectives of this paper are to describe and compare the sampling strategies used to recruit migrant workers from specific migrant groups working in Australia into a cross-sectional study designed to produce population estimates of workplace hazards and self-reported health.

          Results

          Two cross sectional telephone surveys were conducted with immigrants currently working in Australia. Survey 1 used quota sampling from lists provided by a sample broker. Survey 2 used a combination of probability and non-probability sampling, including random sampling from telephone lists. Data from the surveys were weighted and comparisons made with unweighted data. While weighting adjusted for most differences across the sample sources, the likelihood of exposure to workplace hazards depended on exposure types and sampling strategies. We concluded that by using a combination of sampling strategies it is possible to recruit immigrants from specific migrant groups and provide a balanced view of working conditions, although no one strategy was best for all types of measures. Access to a robust sample source for migrants would enable a better perspective to migrant populations’ working conditions.

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          Most cited references32

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          A comparison of goodness-of-fit tests for the logistic regression model.

          Recent work has shown that there may be disadvantages in the use of the chi-square-like goodness-of-fit tests for the logistic regression model proposed by Hosmer and Lemeshow that use fixed groups of the estimated probabilities. A particular concern with these grouping strategies based on estimated probabilities, fitted values, is that groups may contain subjects with widely different values of the covariates. It is possible to demonstrate situations where one set of fixed groups shows the model fits while the test rejects fit using a different set of fixed groups. We compare the performance by simulation of these tests to tests based on smoothed residuals proposed by le Cessie and Van Houwelingen and Royston, a score test for an extended logistic regression model proposed by Stukel, the Pearson chi-square and the unweighted residual sum-of-squares. These simulations demonstrate that all but one of Royston's tests have the correct size. An examination of the performance of the tests when the correct model has a quadratic term but a model containing only the linear term has been fit shows that the Pearson chi-square, the unweighted sum-of-squares, the Hosmer-Lemeshow decile of risk, the smoothed residual sum-of-squares and Stukel's score test, have power exceeding 50 per cent to detect moderate departures from linearity when the sample size is 100 and have power over 90 per cent for these same alternatives for samples of size 500. All tests had no power when the correct model had an interaction between a dichotomous and continuous covariate but only the continuous covariate model was fit. Power to detect an incorrectly specified link was poor for samples of size 100. For samples of size 500 Stukel's score test had the best power but it only exceeded 50 per cent to detect an asymmetric link function. The power of the unweighted sum-of-squares test to detect an incorrectly specified link function was slightly less than Stukel's score test. We illustrate the tests within the context of a model for factors associated with low birth weight.
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            Effective recruitment and retention of minority research participants.

            Our ability, as leaders in public health scholarship and practice, to achieve and measure progress in addressing racial/ethnic disparities in health status and health care is severely constrained by low levels of participation of racial/ethnic minority populations in health-related research. Confining our review to those minority groups federally defined as underrepresented (African Americans/blacks, Latinos/Hispanics, and Native Americans/American Indians), we identified 95 studies published between January 1999 and April 2005 describing methods of increasing minority enrollment and retention in research studies, more than three times the average annual output of scholarly work in this area during the prior 15-year period. Ten themes emerged from the 75 studies that were primarily descriptive. The remaining 20 studies, which directly analyzed the efficacy or effectiveness of recruitment/retention strategies, were examined in detail and provided useful insights related to four of the ten factors: sampling approach/identification of targeted participants, community involvement/nature and timing of contact with prospective participants, incentives and logistical issues, and cultural adaptations. We then characterized the current state of this literature, discussing implications for future research needs and directions.
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              The impact of methodological moderators on prevalence rates of workplace bullying. A meta-analysis

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                Author and article information

                Contributors
                alison.reid@curtin.edu.au
                Journal
                BMC Res Notes
                BMC Res Notes
                BMC Research Notes
                BioMed Central (London )
                1756-0500
                7 October 2020
                7 October 2020
                2020
                : 13
                : 473
                Affiliations
                GRID grid.1032.0, ISNI 0000 0004 0375 4078, School of Public Health, , Curtin University, ; GPO Box U1987, Perth, WA 6845 Australia
                Article
                5320
                10.1186/s13104-020-05320-x
                7542909
                33028419
                254654de-668f-48e3-a8cc-0722879ca8de
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 28 August 2020
                : 30 September 2020
                Funding
                Funded by: Australian Research Council Discovery Project
                Award ID: #DP160100660
                Award Recipient :
                Categories
                Research Note
                Custom metadata
                © The Author(s) 2020

                Medicine
                migrant workers,cross-sectional surveys,sampling,methods
                Medicine
                migrant workers, cross-sectional surveys, sampling, methods

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